What metrics can be used to evaluate the performance of a regression model?

Question

Accepted Answer

Various metrics like Mean Squared Error, R-squared, Mean Absolute Error can be used to evaluate regression model performance.

Mean Squared Error (MSE) - measures the average of the squares of the errors or deviations
R-squared (R2) - indicates the proportion of the variance in the dependent variable that is predictable from the independent variables
Mean Absolute Error (MAE) - measures the average of the absolute errors between predicted and actual values
Root Mean Squared Error (RMSE) - square root of the average of the squared differences between predicted and actual values

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